• Title/Summary/Keyword: 확률적 신뢰구간

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중도절단된 생존함수의 신뢰구간 비교연구

  • Lee, Gyeong-Hwa;Lee, Jae-Won
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.05a
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    • pp.251-255
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    • 2005
  • 중도절단된 자료와 표본수가 적은 자료를 가지는 생존분석에서 생존율을 추정하거나 두 집단의 생존율을 비교할 때 정규분포 근사를 가정한 신뢰구간을 이용하는 데는 많은 어려움이 생긴다. 생존함수의 신뢰구간에 대한 중도절단을, 표본의 크기에 따른 다양한 상황의 모의실험을 통하여 Kaplan-Meier, Nelson, 적률 추정량 그리고 cox model의 ${\beta}$을 가지고 붓스트랩을 이용한 신뢰구간과 비모수 신뢰구간, 우도비 신뢰구간의 실제 포함 확률을 비교해보고자 한다.

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Estimation of confidence interval in exponential distribution for the greenhouse gas inventory uncertainty by the simulation study (모의실험에 의한 온실가스 인벤토리 불확도 산정을 위한 지수분포 신뢰구간 추정방법)

  • Lee, Yung-Seop;Kim, Hee-Kyung;Son, Duck Kyu;Lee, Jong-Sik
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.4
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    • pp.825-833
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    • 2013
  • An estimation of confidence intervals is essential to calculate uncertainty for greenhouse gases inventory. It is generally assumed that the population has a normal distribution for the confidence interval of parameters. However, in case data distribution is asymmetric, like nonnormal distribution or positively skewness distribution, the traditional estimation method of confidence intervals is not adequate. This study compares two estimation methods of confidence interval; parametric and non-parametric method for exponential distribution as an asymmetric distribution. In simulation study, coverage probability, confidence interval length, and relative bias for the evaluation of the computed confidence intervals. As a result, the chi-square method and the standardized t-bootstrap method are better methods in parametric methods and non-parametric methods respectively.

Confidence Interval for Sensitive Binomial Attribute : Direct Question Method and Indirect Question Method (민감한 이항특성에 대한 신뢰구간 : 직접질문법과 간접질문법)

  • Ryu, Jea-Bok
    • The Korean Journal of Applied Statistics
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    • v.28 no.1
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    • pp.75-82
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    • 2015
  • We discuss confidence intervals for sensitive binomial attributes obtained by a direct question method and indirect question method. The Randomized Response Technique(RRT) by Warner (1965) is an indirect question method that uses a randomization device to reduce the response burden of respondents. We used the mean coverage probability (MCP), root mean squared error (RMSE), and mean expected width (MEW) to compare the confidence intervals by the two methods. The numerical comparisons indicated found that the MEW of RRT is too large and the RRT is so conservative that the MCP exceeds a nominal level(${\alpha}$); therefore, it is necessary to complement these problem in order to increase the utility of the indirect question method.

Confidence Intervals for a tow Binomial Proportion (낮은 이항 비율에 대한 신뢰구간)

  • Ryu Jae-Bok;Lee Seung-Joo
    • The Korean Journal of Applied Statistics
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    • v.19 no.2
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    • pp.217-230
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    • 2006
  • e discuss proper confidence intervals for interval estimation of a low binomial proportion. A large sample surveys are practically executed to find rates of rare diseases, specified industrial disaster, and parasitic infection. Under the conditions of 0 < p ${\leq}$ 0.1 and large n, we compared 6 confidence intervals with mean coverage probability, root mean square error and mean expected widths to search a good one for interval estimation of population proportion p. As a result of comparisons, Mid-p confidence interval is best and AC, score and Jeffreys confidence intervals are next.

Comparison of Some Nonparametric Statistical Inference for Logit Model (로짓모형의 비모수적 추론의 비교)

  • 정형철;김대학
    • The Korean Journal of Applied Statistics
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    • v.15 no.2
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    • pp.355-366
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    • 2002
  • Nonparametric statistical inference for the parameter of logit model were examined. Usually nonparametric approach is milder than parametric approach based on normal theory assumption. We compared the two nonparametric methods for legit model, the bootstrap and random permutation in the sense of coverage probability. Monte Carlo simulation is conducted for small sample cases. Empirical power of hypothesis test and coverage probability for confidence interval estimation were presented for simple and multiple legit model respectively. An example were also introduced.

Bootstrap confidence interval for survival function in the Koziol-Green model (KOZIOL-GREEN 모형에서 생존함수에 대한 붓스트랩 구간추정)

  • 조길호;정성화;최달우;최현숙
    • The Korean Journal of Applied Statistics
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    • v.11 no.1
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    • pp.151-161
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    • 1998
  • We study the bootstrap interval estimation for survival function in the Koziol-Green model. We construct the approximate bootstrap confidence intervals for survival function and prove the strong consistency for the bootstrap estimator of survival function. Finally we show that the approximate bootstrap confidence intervals are better in terms of coverage probability than confidence intervals based on asymptotic normal distribution and transformations of survival function via Monte Carlo simulation study.

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Bayesian Interval Estimation of Tobit Regression Model (토빗회귀모형에서 베이지안 구간추정)

  • Lee, Seung-Chun;Choi, Byung Su
    • The Korean Journal of Applied Statistics
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    • v.26 no.5
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    • pp.737-746
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    • 2013
  • The Bayesian method can be applied successfully to the estimation of the censored regression model introduced by Tobin (1958). The Bayes estimates show improvements over the maximum likelihood estimate; however, the performance of the Bayesian interval estimation is questionable. In Bayesian paradigm, the prior distribution usually reflects personal beliefs about the parameters. Such subjective priors will typically yield interval estimators with poor frequentist properties; however, an objective noninformative often yields a Bayesian procedure with good frequentist properties. We examine the performance of frequentist properties of noninformative priors for the Tobit regression model.

Assessment of uncertainty associated with parameter of gumbel probability density function in rainfall frequency analysis (강우빈도해석에서 Bayesian 기법을 이용한 Gumbel 확률분포 매개변수의 불확실성 평가)

  • Moon, Jang-Won;Moon, Young-Il;Kwon, Hyun-Han
    • Journal of Korea Water Resources Association
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    • v.49 no.5
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    • pp.411-422
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    • 2016
  • Rainfall-runoff modeling in conjunction with rainfall frequency analysis has been widely used for estimating design floods in South Korea. However, uncertainties associated with underlying distribution and sampling error have not been properly addressed. This study applied a Bayesian method to quantify the uncertainties in the rainfall frequency analysis along with Gumbel distribution. For a purpose of comparison, a probability weighted moment (PWM) was employed to estimate confidence interval. The uncertainties associated with design rainfalls were quantitatively assessed using both Bayesian and PWM methods. The results showed that the uncertainty ranges with PWM are larger than those with Bayesian approach. In addition, the Bayesian approach was able to effectively represent asymmetric feature of underlying distribution; whereas the PWM resulted in symmetric confidence interval due to the normal approximation. The use of long period data provided better results leading to the reduction of uncertainty in both methods, and the Bayesian approach showed better performance in terms of the reduction of the uncertainty.

Theoretical Considerations for the Agresti-Coull Type Confidence Interval in Misclassified Binary Data (오분류된 이진자료에서 Agresti-Coull유형의 신뢰구간에 대한 이론적 고찰)

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • v.18 no.4
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    • pp.445-455
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    • 2011
  • Although misclassified binary data occur frequently in practice, the statistical methodology available for the data is rather limited. In particular, the interval estimation of population proportion has relied on the classical Wald method. Recently, Lee and Choi (2009) developed a new confidence interval by applying the Agresti-Coull's approach and showed the efficiency of their proposed confidence interval numerically, but a theoretical justification has not been explored yet. Therefore, a Bayesian model for the misclassified binary data is developed to consider the Agresti-Coull confidence interval from a theoretical point of view. It is shown that the Agresti-Coull confidence interval is essentially a Bayesian confidence interval.

Robust confidence interval for random coefficient autoregressive model with bootstrap method (붓스트랩 방법을 적용한 확률계수 자기회귀 모형에 대한 로버스트 구간추정)

  • Jo, Na Rae;Lim, Do Sang;Lee, Sung Duck
    • The Korean Journal of Applied Statistics
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    • v.32 no.1
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    • pp.99-109
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    • 2019
  • We compared the confidence intervals of estimators using various bootstrap methods for a Random Coefficient Autoregressive(RCA) model. We consider a Quasi score estimator and M-Quasi score estimator using Huber, Tukey, Andrew and Hempel functions as bounded functions, that do not have required assumption of distribution. A standard bootstrap method, percentile bootstrap method, studentized bootstrap method and hybrid bootstrap method were proposed for the estimations, respectively. In a simulation study, we compared the asymptotic confidence intervals of the Quasi score and M-Quasi score estimator with the bootstrap confidence intervals using the four bootstrap methods when the underlying distribution of the error term of the RCA model follows the normal distribution, the contaminated normal distribution and the double exponential distribution, respectively.